When Is Antipsychotic Polypharmacy Supported by Research Evidence? Implications for QI

Background: Concurrent use of multiple standing antipsychotics (antipsychotic polypharmacy) is increasingly common among both inpatients and outpatients. Although this has often been cited as a potential quality-of-care problem, reviews of research evidence on antipsychotic polypharmacy have not distinguished between appropriate versus inappropriate use. Methods A MEDLINE search from 1966 to December 2007 was completed to identify studies comparing changes in symptoms, functioning, and/or side effects between patients treated with multiple antipsychotics and patients treated with a single antipsychotic. The studies were reviewed in two groups on the basis of whether prescribing was concordant with guideline recommendations for multiple-antipsychotic use. Results A review of the literature, including three randomized controlled trials, found no support for the use of antipsychotic polypharmacy in patients without an established history of treatment resistance to multiple trials of monotherapy. In patients with a history of treatment resistance to multiple monotherapy trials, limited data support antipsychotic polypharmacy, but positive outcomes were primarily found in studies of clozapine augmented with a second-generation antipsychotic. Discussion Research evidence is consistent with the goal of avoiding antipsychotic polypharmacy in patients who lack guideline-recommended indications for its use. The Joint Commission is implementing a core measure set for Hospital-Based Inpatient Psychiatric Services. Two of the measures address antipsychotic polypharmacy. The first measure assesses the overall rate. The second measure determines whether clinically appropriate justification has been documented supporting the use of more than one antipsychotic medication

Scientific drilling projects in ancient lakes: integrating geological and biological histories

Sedimentary sequences in ancient or long-lived lakes can reach several thousands of meters in thickness and often provide an unrivalled perspective of the lake's regional climatic, environmental, and biological history. Over the last few years, deep drilling projects in ancient lakes became increasingly multi- and interdisciplinary, as, among others, seismological, sedimentological, biogeochemical, climatic, environmental, paleontological, and evolutionary information can be obtained from sediment cores. However, these multi- and interdisciplinary projects pose several challenges. The scientists involved typically approach problems from different scientific perspectives and backgrounds, and setting up the program requires clear communication and the alignment of interests. One of the most challenging tasks, besides the actual drilling operation, is to link diverse datasets with varying resolution, data quality, and age uncertainties to answer interdisciplinary questions synthetically and coherently. These problems are especially relevant when secondary data, i.e., datasets obtained independently of the drilling operation, are incorporated in analyses. Nonetheless, the inclusion of secondary information, such as isotopic data from fossils found in outcrops or genetic data from extant species, may help to achieve synthetic answers. Recent technological and methodological advances in paleolimnology are likely to increase the possibilities of integrating secondary information, e.g., through molecular dating of molecular phylogenies. Some of the new approaches have started to revolutionize scientific drilling in ancient lakes, but at the same time, they also add a new layer of complexity to the generation and analysis of sediment core data. The enhanced opportunities presented by new scientific approaches to study the paleolimnological history of these lakes, therefore, come at the expense of higher logistic, communication, and analytical efforts. Here we review types of data that can be obtained in ancient lake drilling projects and the analytical approaches that can be applied to empirically and statistically link diverse datasets for creating an integrative perspective on geological and biological data. In doing so, we highlight strengths and potential weaknesses of new methods and analyses, and provide recommendations for future interdisciplinary deep drilling projects